基于语言动机的词汇网自动形态分析

Tom Richens
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引用次数: 1

摘要

NLP系统的性能只能和它们所使用的词汇资源一样好。通过对语言进化结构的建模,可以丰富这些资源的形态和语义。从CatVar数据库中制定了一组语言信息形态学规则,在WordNet的Java模型中实现,并对后缀和脱后缀进行了测试。本文对“过代”和“欠代”进行了测量,并提出了利用多语言资源来改善这些问题的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Linguistically-Motivated Automatic Morphological Analysis for Wordnet Enrichment
Performance of NLP systems can only be as good as the lexical resources they employ. By modelling the evolved structure of language, there is scope for morpho-semantic enrichment of these resources. A set of linguistically-informed morphological rules is formulated from the CatVar database, implemented in a Java model of WordNet and tested on suffixation and desuffixation. Overgeneration and undergeneration are measured and an approach to improving these by using multilingual resources is proposed.
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